Comparison of time-variant coherence algorithms in single-trial: a dynamic analysis

Synchronization in the electroencephalogram, which can be quantified by time-variant coherence measures, reveals a communication between brain regions reflecting different functions (e.g. learning or memory). Aim of this work is to compare three time-variant coherence algorithms in single-trial. The first algorithm is based on the short-time Fourier transform, the second one on the adaptive discrete Fourier transform, whereas the third algorithm is based on a recursive smoothed pseudo Wigner-distribution. Parameters which describe the dynamic properties of the algorithms were calculated and compared on simulated data. Differences were observed in the estimation performance of the algorithms. Based on the obtained results, the algorithms are discussed for their utilization in future applications.

Analysis of time-variant quadratic phase couplings in the tracé alternant EEG by recursive estimation of 3rd-order time–frequency distributions

The quantification of transient quadratic phase couplings (QPC) by means of time-variant bispectral analysis is a useful approach to explain several interrelations between signal components. A generalized recursive estimation approach for 3rd-order time-frequency distributions (3rd-order TFD) is introduced. Based on 3rd-order TFD, time-variant estimations of biamplitude (BA), bicoherence (BC) and phase bicoherence (PBC) can be derived. Different smoothing windows and local moment functions for an optimization of the estimation properties are investigated and compared. The methods are applied to signal simulations and EEG signals, and it can be shown that the new time-variant bispectral analysis results in a reliable quantification of QPC in the tracé alternant EEG of healthy neonates.